Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add swan-gtm/gtm-skills --skill event-room-intelligencegit clone --depth 1 https://github.com/swan-gtm/gtm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/swan-gtm/gtm-skills/event-room-intelligence)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/event-room-intelligence"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/event-room-intelligence/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/event-room-intelligence"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/event-room-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00167 | $0.02186 |
| Opus 5 | $0.00084 | $0.01093 |
| Sonnet 5 | $0.00033 | $0.00437 |
| Haiku 4.5 | $0.00017 | $0.00219 |
Grade A, and why
event-room-intelligence scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Event room intelligence
Runs 1 to 3 days before a face-to-face event, as soon as the registration export exists. Produces a phone-readable PDF dossier, one account per page, that the people walking the floor read on the way in: who the buyer is at every account in the room, whether they are physically there, and the one-line play.
Template placeholders
Replace every {{...}} before running. The card-anatomy reference lists them with defaults.
{{PRODUCT}}- Your product's name{{CRM}}- Your CRM; read live, never from an export{{PROFILE_LOOKUP}}- Your LinkedIn profile lookup (URL scrape plus name-and-company profile search). Must return photo, current headline, current employer, work email{{COMPANY_LOOKUP}}- Your company enrichment for employee count, total raised, last round{{HUNT_TIER}}- The tier that makes an account a hunt target when someone from it is in the room (default: Gold and above at MQL stage){{LARGE_COMPANY_FLOOR}}- Size above which an untiered company still gets a full card (default: 200+ employees or $50M+ raised){{DEMOTE_LIST}}- Giant, well-known logos that stay in the dossier but move to the end of the cold list (enterprise-gated, or no buyer in the room){{COMPETITORS}}- Competitors; they get a watch-list line, never a card{{ALIAS_LIST}}- Your maintained registrant-name-to-domain overrides, grown event over event{{LOOKUP_BATCH}}- Companies per enrichment sub-agent when sizing fans out (default: 12){{FLOOR_TEAM}}- Who from your side attends and reads the dossier
Inputs (ask once)
The registration export (name, email, approval status, and whatever title, company, and LinkedIn fields the form collected), the event date, who from {{FLOOR_TEAM}} attends, and the goal: hunt deals, meet customers, or recruit. Everything else is derived.
Phase 1 - Map every registrant to a company
Run the waterfall in order and record which rung matched, because the rung sets the confidence you show on the card:
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 92 lines · 167 tokens per session scan A 45a55eedef14
event-room-intelligence is a skill published in the GitHub repository swan-gtm/gtm-skills (150 stars, last pushed 2d ago), licensed MIT. It adds 167 tokens to every session and 2,186 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-11.
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